Water is a Short Blanket" or "Zero Sum" Problem in the U.S. West

Water issues in the intermountain U.S. west or many other places are a “short blanket” problem, a zero-sum economic issue where there is not enough of a vital asset and Improving one outcome automatically worsens another. 

Water policies sometimes also embody irrational economic choices. Consider that “the average price of water paid by agricultural purchasers across the three states, weighted by volume, was $30.32 per acre-foot,” according to a study by the UCLA Institute of the

Environment and Sustainability. 

“The average price of water paid by municipal entities, weighted by volume, was $512.01 per acre-foot.”

So the wholesale price charged to water suppliers serving city customers was nearly 17 times higher than charged to agricultural customers. 

UCLA Institute of the Environment and Sustainability 

Agriculture also represents most of the water use. Agriculture accounts for roughly 70- to 80 percent of water use in the Colorado River Basin and similar Western systems. 

In other words, residential rates equate to hundreds or thousands of dollars per acre foot ($3/1,000 gal ≈ $977/AF before fixed charges or higher tiers), where agricultural users pay perhaps $30 per acre foot.

Actual household bills also embed system-wide costs that agricultural users often avoid.

And, to be sure, residential customers pay for fully treated, pressurized, reliable delivery plus system upkeep. 

Agricultural rates often cover only diversion or basic delivery of untreated water. 

Fixed charges, tiered residential rates (designed to discourage high use), and pumping surcharges further raise household bills.

Location / Entity	User Type	Approximate Rate	Notes / Context	Source Example
Lower Colorado River Basin (AZ/CA/NV aggregate)	Agricultural districts (wholesale)	~$30/AF average (many $0–few $/AF)	Weighted average; large volumes at $0 via federal contracts (e.g., IID, Coachella, Palo Verde, Truckee-Carson, Unit B)	UCLA/NRDC report
Lower Colorado River Basin (AZ/CA/NV aggregate)	Municipal utilities (wholesale)	~$512/AF average	Same water sources; higher for California coastal/municipal	UCLA/NRDC report
Imperial Irrigation District (CA, major Colorado River user)	Agricultural	~$20/AF (district charge to farmers)	District itself pays $0 to federal government for water	Reporting on UCLA study / district statements
Denver Water (CO)	Residential (volumetric, inside city)	~2.90–6.96 per 1,000 gal (tiered; higher outside city)	Plus fixed meter charges (~$19+ for small meters); effective household rates higher with typical use	Denver Water rate schedules
Salt Lake City area / Utah examples	Residential	Often in the range of a few $/1,000 gal + base; monthly bills for moderate use commonly tens of dollars	Utah cities noted for relatively lower excessive-use rates vs. some neighbors in older comparisons; varies widely by provider	Utility comparisons & rate sheets
Phoenix (AZ)	Residential	Seasonal volumetric (e.g., ~4.93–6.13 per unit after included allowance) + service charge	Units often ~748 gal; includes environmental charges; bills vary strongly by season/use	City of Phoenix rate documents
Las Vegas Valley / Southern Nevada	Residential	Higher effective rates in comparative surveys (e.g., tens of $ for moderate monthly use)	Relies on Colorado River; strong conservation incentives	Comparative rate surveys
Various Intermountain municipal (e.g., Idaho, Utah examples)	Residential	Base + $1–several $ per 1,000 gal common; monthly costs for 10k–20k gal often $30–100+ depending on location/tiers	Highly variable; some flat or low-tier structures	Local utility rate comparisons (Ammon ID area, Mountain Regional UT, etc.)
Federal Reclamation Colorado River deliveries	Ag vs. others	~$0.12/AF weighted average (federal)	Contrasts with non-federal sources averaging hundreds of $/AF	UCLA/NRDC

Still, the inescapable point is that the economics of water pricing do not encourage water conservation by the users of 70 percent to 80 percent of all the water. 

In fact, western water use rights actually encourage agricultural consumption, as any reductions risk losing future allocations. 

So water conservation in the arid U.S. intermountain region can be a frustrating exercise. 

In the current drought, it seems that residential water usage has been cut about five percent, though water managers were aiming for 20 percent reductions.

Some of us might argue that 20-percent reductions are not feasible, for a number of reasons. Since 2000:

• Population has grown as much as 40 percent but water consumption in the Denver metro area has declined 30 percent to 38 percent

• Citizens consume only seven percent of Colorado’s water

• Agriculture accounts for 89 percent of the total water consumed within Colorado.

source: Water Education Colorado

 

What nobody wants to discuss, much less do, is focus on reducing water use by the users of 70 percent to 80 percent of the water. 

As much as most people would prefer to support local agriculture, there are probably real limits to how much more water savings are possible in urban areas, given population growth and reduced consumption already between 30 percent and 38 percent. 

The point is that there simply are limits to how much less water consumers can routinely be expected to use. 

The core obstacles include western water law’s “prior appropriation” system. Basically, that creates a “use it or lose it” system with strong disincentives for senior (priority) right holders to conserve.

Among the key issues:

• Prior appropriation (“first in time, first in right”): In most western states, senior appropriators get their full allocation before juniors get any in dry years

• Use it or lose it: Many states presume abandonment or allow cancellation of rights after years of non‑use (five years in Oregon, 10 in Colorado) 

• Beneficial-use and diversion requirements: Rights are often defined by a specific place of diversion, place of use, and type of use. Conserving by changing crops, fallowing, or switching to efficient irrigation can trigger administrative review and risk losing flexibility or volume if the saved water is not legally “owned” by the conserved

• Third‑party injury and transfer hurdles: Even when conservation is allowed, moving saved water to other uses (including instream flows) can be blocked by protests from other users concerned about return flows and hydrologic impacts, making transactions slow and uncertain 

The result of misaligned rules is “defensive” overuse, such as irrigating even when uneconomic or maintaining low‑value crops, as  the legal right is more valuable than the annual crop. 

Feature	Colorado	Oregon	Nevada	Montana	California
Non-use period triggering risk	10 years (rebuttable presumption of abandonment)	5 successive years (rebuttable presumption of forfeiture)	5 successive years for groundwater; surface water follows abandonment only	10 successive years (prima facie presumption of abandonment)	5 years (reversion to public upon Board finding)
Legal standard	Requires intent plus non-use; lacks statutory forfeiture	Forfeiture statute (no intent required)	Statutory forfeiture for groundwater; abandonment for surface water	Presumption of abandonment created by statute	Statutory forfeiture; may require a competing claim
Efficiency-upgrade exemption	No dedicated exemption; offers conservation program tolling	Protected if facility remains capable and ready	No specific exemption, though conservation aids extensions	No dedicated exemption; set-aside programs are protected	Conservation deemed reasonable beneficial use; no forfeiture
Conservation mechanisms	Instream flow loans, water banking, and environmental contracts	Allocated Conserved Water Program and instream leases	Temporary change-of-use permits and extension reviews	Instream leasing and temporary flow changes	Instream flow dedication and temporary urgency changes
Priority preserved?	Yes; original priority date remains intact	Yes; original or slightly junior dates for certificates	Subject to Engineer approval; no dedicated leasing statute	Yes; FWP leases maintain their original priority	Yes; instream dedications preserve existing priority

source: Perplexity analysis 

The perhaps-obvious solution is to change the rules:

• Statutory “conservation credits” and safe harbors: Laws that let users keep ownership of water they save through efficiency (rather than risking forfeiture) 

• Flexible leasing and temporary transfers: Short‑term leases of water that let rights holders reduce use without abandoning the right 

• Strategic water reserves and state purchases: Letting states or others lease or buy high‑priority rights to maintain streamflows, recharge aquifers, or retire pumping

• Demand‑side management; crop or portfolio shifts: Shift to higher‑value/less‑water‑intensive crops 

The longer-term issue is harder to avoid. Agriculture in the arid U.S. west is challenged by the lack of water. Under the best of circumstances, the U.S. intermountain west is simply arid, as are the Great Plains (west of the 100th meridian). 

source: Environmental Defense Fund 

This is a short-blanket problem for sure. 

Nvidia Asset-Backed "Securitization" Moves

Nvidia is working with six private equity and financial entities to create a financing mechanism for servers that essentially aims to turn hardware capex  into infrastructure. 

Nvidia signed memorandums of understanding with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR. 

The partners will assemble capital pools at rates Nvidia characterized as attractive, with intended beneficiaries spanning frontier AI labs, enterprises, and cloud providers. 

The commercial aim is to enable compute buyers to obtain capacity without showing that “capex” on balance sheets, much as an airline leases aircraft rather than buying planes.

In other words, the mechanism shifts server and compute hardware depreciation schedules to longer-lived categories similar to commercial real estate or toll roads. 

Essentially, the effort aims to effectively securitize compute, functionally if not in a textbook form. 

“Securitization” means a special purpose vehicle pools financial assets such as loans, leases, or receivables, then issues notes whose repayment comes principally from those pooled cash flows. 

There are other similar forms that accomplish the same ends, if not using precisely the same means. 

Structure	What investors finance	Is it securitization?
Equipment-secured loan	GPU servers and sometimes customer contracts	No; it is secured/private credit
Direct infrastructure or project loan	Data center, power, cooling, and network assets	No; it is project finance
SPV ownership plus lease	SPV owns GPUs/data center and leases compute capacity to an operator	Not automatically
Sale-leaseback	A sponsor sells assets to an SPV and leases them back	Not automatically
Asset-Backed Securities (ABS) and Commercial Mortgage-Backed Securities (CMBS)	Pool of GPU leases, compute receivables, data-center loans, or tenant leases	Yes, or close economic analogy

The model resembles aircraft-lease or equipment forms of asset-backed securities, where: a bankruptcy-remote vehicle owns equipment and receives contractual lease or service payments. 

Equipment ABS also have been used to finance shipping, and rail assets as well. 

That, in turn, will help customers access scarce compute at scale by moving such compute capabilities off the balance sheet, in principle alleviating investor concern about the timing of AI capital expenditure and near-term financial returns.

How Big a Problem is Buyer Concentration in the AI Value Chain?

If OpenAI and Anthropic drive 48 percent of Google Cloud revenue in 2027, is that a problem?

• Some might say “yes,” to the degree that customer concentration is generally viewed as a problem. 

• Others might say “maybe,” if customer concentration or solvency danger is not ameliorated.

• But the history of computing might suggest “no” is a possible answer, as there are parallels in mainframes, supercomputers, military computing, and even early semiconductors.

The closest historical analogy is probably the mainframe/supercomputer market of the 1960s to 1980s. 

The current AI infrastructure boom therefore looks less like the PC industry and more like an earlier era when a computer system could be a multimillion-dollar capital project.

The interesting question is not simply "Are there few buyers?" There are. It is why there are few buyers and what dimensions of concentration matter.

In the 1950s and 1960s, computers were so expensive that the customer base was intrinsically concentrated.

IBM's 1401, introduced in 1959, in the mid-1960s, represented more than half of the world's computers. The IBM System/360 arguably deepened the pattern, as a relatively small number of customers represented a very large percentage of industry revenue.

Early on, government was an extraordinarily important buyer of such computers, for example. 

There also are parallels in the semiconductor industry, where  military and aerospace customers were key. 

NASA's Apollo program, for example, purchased roughly 60 percent of U.S. integrated-circuit output in the early 1960s.

And the Minuteman missile program subsequently became an even larger individual consumer of ICs.

Of course, skeptics will argue that was different as the U.S. federal government was in no danger of defaulting, where OpenAI or Anthropic are not immune from that outcome.

In the context of demand for high-performance computing services, though, optimists might argue we must separate the small number of direct buyers from the much-larger end-user demand.

The number of organizations using HPC can be much larger than the number actually buying the infrastructure, for example, even if a few buyers stand out. 

So today's AI compute services market resembles other industries where direct buyers are few, such as:

• aircraft;

• electric utilities;

• telecommunications infrastructure;

• semiconductor fabs;

• power generation.

The closest non-computing analogy may actually be aircraft, where large commercial aircraft are sold to a relatively small number of airlines.

In that sense, the small number of passenger airline providers represents an aggregation of relatively large and dispersed  demand. 

That arguably resembles Nvidia selling to a few hyperscalers whose customers are highly concentrated at the moment, but also representing lots of dispersed enterprise demand. 

There might also be similarities to telecommunications or power generation, where a concentrated buyer base is not necessarily evidence of a small market.

In essence, there is a two-level demand structure, with a few key buyers (frontier language model suppliers) supporting a relatively small number of large HPC suppliers, which in turn support end-user demand that is highly distributed.

And, of course, optimists say the market will broaden over time. 

Era	Principal buyers	Buyer concentration
1940s–50s	Military, government, universities	Extreme
1960s mainframes	Government + very large corporations	Very high
1960s supercomputers	Government, defense, scientific institutions	Extreme
1970s–80s minicomputers	Corporations, universities, government	High → falling
1980s–90s PCs	Millions of businesses/consumers	Low
1990s–2000s servers	Businesses, Internet companies	Moderate
2010s cloud	Large enterprises + hyperscalers	Increasing
2020s AI/HPC	Hyperscalers + frontier AI + governments	Very high at infrastructure layer
Ultimate AI consumption	Potentially billions of people and millions of organizations	Potentially very low

The point is that customer concentration in computing is not unusual, especially at early stages of deployment.

Aside from the resemblance to mainframe, minicomputer, integrated circuit precedents, HPC might also suggest parallels to railroads, electric utilities and telephone service industries, where a small number of infrastructure buyers also has been key. 

Are there risks? Yes. But are the risks also manageable over time and structurally consistent with other capital-intensive industries? Perhaps also yes.